# export OMP_NUM_THREADS=8
# export NCCL_IB_DISABLE=0
# export NCCL_IB_GID_INDEX=3
# export NCCL_SOCKET_IFNAME=eth0
# export NCCL_DEBUG=INFO

LLM_VERSION="Qwen/Qwen2-7B-Instruct" 
# for 7b model we recommend bs=1, accum=2, 16 nodes, 128 gpus, lr=1e-5, warmup=0.03
# for 72b model we recommend bs=1, accum=1, 32 nodes, 256 gpus, lr=1e-5, warmup=0.03
# LLM_VERSION_CLEAN="${LLM_VERSION//\//_}"
VISION_MODEL_VERSION="google/siglip-so400m-patch14-384"

############### Pretrain ################

PROMPT_VERSION="qwen_1_5"
RUN_NAME=0925-shot2story_instruction
CKPT_PATH="lmms-lab/llava-onevision-qwen2-7b-ov" # this could also be the previous stage checkpoint
mkdir -vp checkpoints/${RUN_NAME}

# ACCELERATE_CPU_AFFINITY=1 \
CUDA_VISIBLE_DEVICES=0,2,4,5 \
torchrun --nproc_per_node 4 \
    llava/train/train_mem.py \
    --deepspeed scripts/zero3.json \
    --model_name_or_path ${CKPT_PATH} \
    --vision_tower ${VISION_MODEL_VERSION} \
    --version ${PROMPT_VERSION} \
    --data_path ./onevision_data/annotations/shot2story_instruct.json \
    --image_folder ./onevision_data/images \
    --video_folder ./onevision_data/videos \
    --video_fps 2 --mm_spatial_pool_stride 4 \
    --mm_tunable_parts "mm_mlp_adapter" \
    --lora_enable true \
    --lora_r 16 --lora_alpha 32 \
    --mm_projector_type mlp2x_gelu \
    --mm_vision_select_layer -2 \
    --mm_use_im_start_end False \
    --mm_use_im_patch_token False \
    --group_by_modality_length True \
    --image_aspect_ratio anyres_max_9 \
    --image_grid_pinpoints  "(1x1),...,(6x6)" \
    --mm_patch_merge_type spatial_unpad \
    --bf16 True \
    --run_name $RUN_NAME \
    --output_dir "checkpoints/${RUN_NAME}" \
    --num_train_epochs 1 \
    --per_device_train_batch_size 1 \
    --per_device_eval_batch_size 4 \
    --gradient_accumulation_steps 16 \
    --evaluation_strategy "no" \
    --save_strategy "steps" \
    --save_steps 500 \
    --save_total_limit 5 \
    --learning_rate 1e-5 \
    --weight_decay 0. \
    --warmup_ratio 0.03 \
    --lr_scheduler_type "cosine" \
    --logging_steps 1 \
    --tf32 True \
    --model_max_length 32768 \
    --gradient_checkpointing True \
    --dataloader_num_workers 4 \
    --lazy_preprocess True \
    --report_to tensorboard \
    --torch_compile True \
    --torch_compile_backend "inductor" \
    --dataloader_drop_last True \
    --frames_upbound 120 \
    > checkpoints/${RUN_NAME}/train.log 2>&1 &

# You can delete the sdpa attn_implementation if you want to use flash attn